Image Augumentations
Import Libraries
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import imageio
import imgaug as ia
%matplotlib inline
from imgaug import augmenters as iaa
Import sample image for augumentation purpose
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image = imageio.imread("/home/jayanthikishore/Downloads/ML_classwork/Week5/image1.png")
print("Original:")
ia.imshow(image)
Image rotation left and right direction with (360/30) times
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newimges =[]
for i in range(12):
j=i+1
print(j,j*30)
rotate = iaa.Affine(rotate=(-30*j, 25))
rotate1 = iaa.Affine(rotate=(-25,30*j))
image_aug = rotate(image=image)
image_aug1 = rotate1(image=image)
newimges.append(image_aug)
newimges.append(image_aug1)
ia.imshow(image_aug1)
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print(len(newimges))
Gaussian Noise
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seq = iaa.Sequential([
iaa.Affine(rotate=(-25, 25)),
iaa.AdditiveGaussianNoise(scale=(30, 90)),
iaa.Crop(percent=(0, 0.4))
], random_order=True)
images_aug = [seq(image=image) for _ in range(20)]
print("Augmented:")
ia.imshow(ia.draw_grid(images_aug, cols=6, rows=2))
Checking shape of the Image
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import numpy as np
np.shape(newimges),np.shape(images_aug)
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Concatinate all the augumented images
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concimges = np.concatenate((newimges, images_aug), axis=0)
np.shape(concimges)
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Save all images into a folder
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import cv2
import os
trial_dir = "/Users/preethamvignesh/Downloads/ML_classwork/"
j=0
for i in range(len(concimges)):
pimge = concimges[i]
j =i +1
#pfname ="trial_"+str(i) + ".png" #png is 5*jpg size
pfname ="augumented_"+str(j) + ".jpg"
#print(pfname)
fname =trial_dir + pfname
print(fname)
#cv2.imwrite(fname,pimge)
cv2.imwrite(fname,cv2.cvtColor(pimge, cv2.COLOR_RGB2BGR))
i+=1
ia.imshow(pimge)
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